Question about nested design

Dear all,

I have a rather theoretical question about nested random effects.
Suppose the design has three levels S(ample), R(eplicate) and M(arker).
M is crossed with both S and R. R is nested in S. M has about 40 levels,
S 206 levels and R 251 levels. The difference in the number of levels
between S and R is rather small because 171 samples have only one
replicate. 22 samples have two replicates and 13 samples have three
replicates. Does it makes sense to add the nested effect of R to the
model? So the random structure would look like (1|M) + (1|S) + (1|S:R).
Or should I better stick to a model without the replicates (1|M) +
(1|S)?
Changing the design to get replicates for all samples is not an option
as that would be too expensive and too much work.

Best regards,

Thierry

------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be
www.inbo.be

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of
data.
~ John Tukey


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